Ahead of the Spring Festival, DeepSeek quickly became a hot topic, garnering widespread attention on social media in just a few days. This sudden surge not only surprised many but also triggered a market chain reaction. Simultaneously, Nvidia’s stock plummeted, raising concerns about its future and prompting significant short-selling activity from some institutions, suggesting a potentially orchestrated scenario.

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DeepSeek is an AI-powered tool focused on optimizing deep learning models, particularly in natural language processing (NLP) and image generation. In the days leading up to Chinese New Year, the project unexpectedly gained significant attention from investors and technical professionals. The team’s performance and demonstrated technological achievements have sparked considerable interest. Discussions about DeepSeek dominate tech circles across developer communities and social media platforms.

However, DeepSeek’s sudden surge in popularity wasn’t accidental. Analysis suggests potential involvement from certain institutions. Notably, Nvidia’s stock price has since seen a clear decline, indicating some factors are driving this change.

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Nvidia, a leading manufacturer of graphics processing units (GPUs), has long been a key hardware provider for large language models and AI computing. While the company’s stock has consistently performed strongly alongside the rapid growth of the AI market, it recently experienced a sharp decline following DeepSeek’s surge in popularity and increased market attention to its technology.

This phenomenon may involve short-selling strategies by institutional investors. In recent years, as AI technology has become widespread, Nvidia’s stock price has been highly inflated, leading many investors to believe its valuation is overhyped. Particularly after the surge in popularity of DeepSeek, some institutions may have profited handsomely by shorting Nvidia’s stock. These institutions successfully capitalized on precise market timing and an understanding of DeepSeek’s influence.

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In traditional AI applications, many practitioners and investors focus on the “results” of AI models—such as generated images or text. However, discussions surrounding DeepSeek reveal a growing recognition that the underlying reasoning chain behind large language models is the more valuable core element. Previously, we could only see model outputs; now, we need to understand their logic, algorithms, and how to optimize performance by adjusting these factors.

This shift in thinking represents a deeper consideration of AI research and application. Moving from simple “black box” operations to genuinely understanding the internal workings of models is prompting many technical experts and investors to re-evaluate the future direction of artificial intelligence. DeepSeek’s popularity exemplifies this breakthrough, encouraging attention towards the entire model construction and optimization process, rather than just the final output.

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DeepSeek’s sudden rise, Nvidia’s stock plunge, and the market manipulation behind it all appear to be part of a carefully orchestrated scheme. A deep understanding of large language model thinking chains reveals that applying AI technology isn’t just about superficial accumulation; it requires in-depth exploration and optimization of internal model logic. As technology advances, we may see more innovative tools like DeepSeek emerge, driving AI research and application to new heights.

This phenomenon not only reveals the immense potential of AI technology but also prompts us to consider the underlying business competition and capital operations. The future market trends will be a continued focus of this interplay between technology and capital.